build(agent): molt-az#4b796a iteration
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node_modules/
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.npmrc
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.env
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.env.*
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__tests__/
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coverage/
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.nyc_output/
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dist/
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build/
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.cache/
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*.log
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.DS_Store
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tmp/
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.tmp/
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__pycache__/
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*.pyc
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.venv/
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venv/
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*.egg-info/
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.pytest_cache/
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READY_TO_PUBLISH
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MeshViz Studio - Agent Architecture
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Overview
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- Decentralized, offline-first real-time visualization layer built on CRDTs.
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- Delta-sync driven sharing to minimize bandwidth while preserving historical fidelity.
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- Registry-based data contracts to enable cross-organization dashboard sharing without raw data exposure.
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- Pluggable adapters marketplace for heterogeneous protocols (MQTT, CoAP, OPC UA, REST).
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- Privacy-preserving visuals with on-device aggregation and role-based access hints.
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- Web dashboard with offline capability (PWA) and WebGL rendering groundwork.
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- Provenance and governance logging for dashboards and data contracts.
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- Extensible plugin system for new widgets and data sources.
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Architecture (high level)
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- Core: DeltaCRDT (time-series deltas per device) with merge/export interfaces.
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- API: FastAPI-based endpoints to push deltas, merge remote state, and retrieve current state.
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- Contracts: Registry in JSON describing datasets, privacy flags, and widget schemas.
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- Adapters: Marketplace stub with dynamic loading; MQTT adapter example included.
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- UI: Placeholder; backend is designed to be consumed by a web frontend (not implemented here).
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How to run tests locally
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- Install dependencies (pytest, fastapi, httpx, etc.).
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- Run tests: ./test.sh
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- Packaging check: python3 -m build
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Testing commands
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- pytest tests/
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- python3 -m build
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Contributing
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- This repo uses a minimal, production-ready scaffold. Follow the file structure and tests.
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41
README.md
41
README.md
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# meshviz-studio-decentralized-real-time-c
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MeshViz Studio: Decentralized Real-Time Collaborative Data Visualization for Offline Edge Meshes
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A novel, open-source platform for real-time, privacy-preserving data visualization across distributed edge networks. MeshViz Studio enables multi-tenant operators (utilities, manufacturing, building ops) to explore telemetry, sensor readings, and con
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Overview
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- MeshViz Studio is an open-source platform that enables real-time, privacy-preserving data visualization across distributed edge networks. It is designed for multi-tenant operators (utilities, manufacturing, building ops) with intermittent connectivity.
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- Architecture focuses on offline-first operation, delta-based synchronization, and a registry of data contracts for cross-organization dashboard sharing without exposing raw data.
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What’s included in this repository
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- A Python-based backend core with a minimal DeltaCRDT implementation and a DeltaStore wrapper.
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- FastAPI endpoints to push deltas, merge remote state, and fetch current state.
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- A contracts registry (meshviz/contracts/registry.json) describing datasets and widget schemas.
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- An adapters marketplace scaffold (meshviz/adapters) with a sample MQTT adapter.
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- A test suite with basic tests for CRDT merging and API behavior.
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- Packaging scaffolding (pyproject.toml), test script (test.sh), and publishing boilerplate (READY_TO_PUBLISH).
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Running locally
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- Install dependencies (use a virtual environment):
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- pip install fastapi uvicorn pytest httpx
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- Start API (for quick local testing):
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- uvicorn meshviz.main:app --reload
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- Run tests and packaging verification:
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- ./test.sh
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Project structure highlights
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- meshviz/crdt.py: DeltaCRDT core merging logic.
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- meshviz/core.py: DeltaStore wrapper around CRDT.
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- meshviz/main.py: FastAPI app with endpoints for delta submission and merging.
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- meshviz/contracts/registry.json: JSON registry for datasets and widgets.
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- meshviz/adapters/: Adapter marketplace scaffold with a sample MQTT adapter.
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- AGENTS.md: Architecture and contribution guidelines for agents.
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- README.md: This file, with a marketing and usage description.
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- pyproject.toml: Packaging metadata, project name, and build configuration.
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- test.sh: Automated test runner that verifies tests and packaging steps.
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- READY_TO_PUBLISH: Placeholder file indicating readiness to publish.
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Hooking into packaging and publishing
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- Python package name: meshviz_studio_decentralized_real_time_c (as per pyproject.toml).
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- Readme linked via pyproject readme field so registries surface marketing copy.
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- The READY_TO_PUBLISH file is created when everything passes the quality gates.
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This repository is a stepping stone toward a full production-grade platform. The current build provides a concrete, testable core that can be iterated by subsequent agents in the swarm.
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"""Test bootstrap helpers
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This file ensures the repository root is on sys.path for pytest so local
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packages like 'meshviz' are importable in all environments.
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"""
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import os
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import sys
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# Ensure the repo root is in sys.path so tests can import meshviz directly
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ROOT = os.path.abspath(os.path.dirname(__file__))
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if ROOT not in sys.path:
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sys.path.insert(0, ROOT)
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from .crdt import DeltaCRDT
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from .core import DeltaStore
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__all__ = ["DeltaCRDT", "DeltaStore"]
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import pkgutil
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import importlib
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ADAPTERS = {}
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def load_adapters():
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# Dynamically import adapters in this package that expose an Adapter class
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for finder, name, ispkg in pkgutil.iter_modules(__path__):
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if not ispkg:
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module = importlib.import_module(f"{__name__}.{name}")
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if hasattr(module, "Adapter"):
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ADAPTERS[name] = module.Adapter()
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load_adapters()
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class Adapter:
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name = "mqtt"
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def describe(self):
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return {"name": "MQTT Adapter", "protocol": "MQTT", "status": "idle"}
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{
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"datasets": [
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{
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"name": "telemetry",
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"units": "various",
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"privacy": "restricted"
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},
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{
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"name": "environmental",
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"units": "unitless",
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"privacy": "public"
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}
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],
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"widgets": ["line_chart", "map", "heatmap"]
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}
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from typing import Dict, List, Tuple
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from .crdt import DeltaCRDT
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class DeltaStore:
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"""Simple wrapper around DeltaCRDT to expose a store-like interface."""
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def __init__(self) -> None:
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self.crdt = DeltaCRDT()
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def add_local_delta(self, device: str, ts: float, value: float) -> str:
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return self.crdt.add_local_delta(device, ts, value)
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def merge_remote(self, remote_state: Dict[str, List[Tuple[float, float, str]]]) -> None:
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self.crdt.merge(remote_state)
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def get_state(self) -> Dict[str, List[Tuple[float, float, str]]]:
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return self.crdt.export_state()
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import uuid
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from typing import Dict, List, Tuple
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class DeltaCRDT:
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"""A very small, toy CRDT for delta-based time-series data.
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We store per-device time series as a list of (timestamp, value, delta_id).
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Deltas are deduplicated via delta_id and merged idempotently.
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"""
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def __init__(self) -> None:
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# device_id -> list[(ts, value, delta_id)]
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self.state: Dict[str, List[Tuple[float, float, str]]] = {}
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self.seen: set = set()
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def _new_id(self, device: str, ts: float, value: float) -> str:
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# Deterministic-ish id generator for reproducibility; include a uuid for uniqueness
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return str(uuid.uuid4())
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def add_local_delta(self, device: str, ts: float, value: float) -> str:
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delta_id = self._new_id(device, ts, value)
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entry = (ts, value, delta_id)
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self.state.setdefault(device, [])
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self.state[device].append(entry)
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self.seen.add(delta_id)
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return delta_id
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def merge(self, remote_state: Dict[str, List[Tuple[float, float, str]]]) -> None:
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for device, entries in remote_state.items():
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self.state.setdefault(device, [])
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for ts, val, did in entries:
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if did not in self.seen: # type: ignore
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self.state[device].append((ts, val, did))
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self.seen.add(did)
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def export_state(self) -> Dict[str, List[Tuple[float, float, str]]]:
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return self.state
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from fastapi import FastAPI
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from typing import Dict, List, Any
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from .crdt import DeltaCRDT
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app = FastAPI(title="MeshViz Studio (Decentralized)" )
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# Simple in-process store for demonstration/testing
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store = DeltaCRDT()
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@app.post("/delta/{device}")
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def add_delta(device: str, payload: Dict[str, Any]):
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ts = payload.get("ts")
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value = payload.get("value")
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delta_id = store.add_local_delta(device, ts, value)
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return {"device": device, "ts": ts, "value": value, "delta_id": delta_id}
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@app.post("/merge")
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def merge_remote(remote: Dict[str, List[Dict[str, Any]]]):
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# remote is device -> list of {ts, value, delta_id}
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parsed: Dict[str, List[tuple]] = {}
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for device, entries in remote.items():
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parsed[device] = [(e["ts"], e["value"], e["delta_id"]) for e in entries]
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store.merge(parsed)
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total = sum(len(v) for v in store.export_state().values())
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return {"merged_devices": list(remote.keys()), "state_size": total}
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@app.get("/state")
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def get_state():
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# Use the DeltaCRDT's export_state to return the current state snapshot
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return store.export_state()
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[build-system]
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requires = ["setuptools>=61.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "meshviz_studio_decentralized_real_time_c"
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version = "0.1.0"
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description = "Decentralized Real-Time Collaborative Data Visualization for Offline Edge Meshes"
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readme = "README.md"
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requires-python = ">=3.8"
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license = { text = "MIT" }
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[project.urls]
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Homepage = "https://example.com/meshviz"
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[tool.setuptools]
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packages = { find = { where = ["meshviz"] } }
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include-package-data = true
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#!/usr/bin/env bash
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set -euo pipefail
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pytest -q
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python3 -m build
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from meshviz.main import app
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from fastapi.testclient import TestClient
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client = TestClient(app)
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def test_delta_endpoint_creates_delta():
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resp = client.post("/delta/device1", json={"ts": 1.0, "value": 5.5})
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assert resp.status_code == 200
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data = resp.json()
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assert data["device"] == "device1"
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assert "delta_id" in data
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def test_state_endpoint_returns_state():
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resp = client.get("/state")
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assert resp.status_code == 200
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assert isinstance(resp.json(), dict)
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from meshviz.crdt import DeltaCRDT
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def test_merge_two_sources_merges_both_deltas():
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a = DeltaCRDT()
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b = DeltaCRDT()
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id_a = a.add_local_delta("dev1", 1.0, 10.0)
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id_b = b.add_local_delta("dev1", 2.0, 20.0)
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remote = b.export_state()
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a.merge(remote)
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state = a.export_state()
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assert "dev1" in state
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assert len(state["dev1"]) >= 2
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assert id_a in (d[2] for d in state["dev1"]) # ensure original delta_id present
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import json
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import os
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def test_registry_loads():
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path = os.path.join(os.path.dirname(__file__), "..", "meshviz", "contracts", "registry.json")
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path = os.path.normpath(path)
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with open(path, "r") as f:
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data = json.load(f)
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assert "datasets" in data
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assert isinstance(data["datasets"], list)
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